Calculation Methodology

Conditions & Scope

Scope: UN Member States Only

The index exclusively analyzes the 193 UN member states (as of 2026). This ensures data reliability and consistency, as partially recognized or unrecognized territories often lack verifiable, up-to-date information.

Accessibility Score (Ease Coefficient)

Visa requirements are categorized into 6 tiers of accessibility, each assigned a specific weight:

1.0 Visa Not Required
0.9 Electronic Authorization (ETA)
0.8 Visa on Arrival
0.7 Electronic Visa (e-Visa)
0.2 Visa Required
0.0 Admission Refused

Coefficients reflect the relative difficulty of entry and may be adjusted in future updates.

Data Sources & Methodology

I used only open data sources and sought a metric that would simultaneously reflect the tourist attractiveness of all countries in the index while ensuring data availability for recent years (preferably with substantial post-COVID data, i.e., after 2020). The compromise solution was the product of tourism's share in service exports and total service exports. This metric has accumulated several years of data since 2020, effectively capturing the most modern trends in tourism.

Primary formula for a single country:

PQI = ( Σ (Si × Ki) / T ) × 100
01
Si (Destination Power)

Derived from World Bank economic data.

Raw Data: Median of (Tourism % of Exports × Total Service Exports $) over 5 years.
Codes: BX.GSR.TRVL.ZS × BX.GSR.NFSV.CD
Logarithmic Scale: Applied to handle exponential differences between economies (e.g., USA vs. Tuvalu).
Vlog = ln(Vraw)
Normalization: Scaling values from 0.01 to 1.0.
Si = 0.01 + ( (Vlog - Min) / (Max - Min) ) × 0.99
02
Ki (Accessibility Score)

The "ease of entry" coefficient (1.0 for Visa-Free, 0.2 for Visa Required, etc.) applied to the destination.

Home Country Included: The calculation includes the home country as a destination (Score 1.0). Citizenship grants unrestricted access to domestic tourism, which is an intrinsic part of global mobility.
03
T (Total Importance)

The sum of "Destination Power" for all countries globally. This represents the theoretical maximum score.

In Plain English:

Imagine global tourism as a pie. PQI measures what percentage of this pie your passport allows you to "taste". Difficult visas (score 0.2) only let you have crumbs, while visa-free access hands you the whole slice.

Formula:

VFE = Median( { Si | Ki ≥ 0.9 } ) × 100
  • Filter: Consider only countries with visa-free or electronic authorization entry (K ≥ 0.9).
  • Exclusion: The home country is excluded from the calculation. This metric assesses diplomatic efficiency, focusing strictly on external destinations and international travel potential.
  • Calculate: Find the median "Destination Power" (Si) of these countries.
  • Scale: Multiply by 100 for readability.
  • Ranking: In the VFE rankings, passports are ordered first by higher VFE. When two passports have the same VFE, the one with fewer visa-free and ETA destinations ranks higher, highlighting efficiency. If both VFE and that destination count are equal, the passport with the lower overall PQI is ranked higher, underscoring that seemingly weaker passports by destination count can still be extremely efficient.
In Plain English:

This represents the "average coolness" of your visa-free and ETA destinations. We line up all the countries you can visit visa-free or with electronic authorization by their tourism power and pick the one right in the middle.

It reveals the quality of a typical country accessible to you without a traditional visa process.

This is a conscious trade-off between precision and sustainability. I maintain this project independently. The current automated classifier allows for validation without a dedicated team.

To accurately account for the nuances of varying e-Visa complexities, I would need:

  • Extremely detailed data for each country.
  • A full team for data collection and validation.
  • Constant monitoring (visa policies change monthly).

I estimate the aggregate impact of such detail to be very low for this ranking system - in practice, the difference would only shift a passport by 2-3 positions within the top 50.

A direct indicator like BX.GSR.TRVL.CD (tourism receipts) from the World Bank is only available up to 2020. If the world hadn't changed so drastically since then, using older data might be acceptable. However, critical shifts have occurred:

  • Post-pandemic recovery.
  • Geopolitical shifts (sanctions, new visa policies).
  • Emergence of new tourism hubs.

Using the product of BX.GSR.TRVL.ZS × BX.GSR.NFSV.CD allows me to derive much fresher data (2020-2024). Crucially, this captures several years of the post-COVID era, better reflecting current tourism trends.

I acknowledge that this product, while algebraically equivalent to tourism receipts, has a margin of error (~8-10%) due to methodological differences in sources (Balance of Payments vs. National Accounts). I consider this an acceptable price for data relevance.

Axiom: No destination has zero tourist or geopolitical significance. I assign a minimal weight (0.01) even to the statistically least demanded destinations.

Using 0 as a minimum would create a mathematical paradox:

Situation
Country X has Si = 0
↓
Any visa requirement (even visa-free) yields zero contribution to PQI.
Paradox
  • Passport A: Visa required for X
  • Passport B: Entry to X completely banned
→ Both receive the same PQI score

In reality, a visa requirement is better than a ban. The minimal value of 0.01 resolves this issue.